Gas recognition using a neural network approach to plasma optical emission spectroscopy

M Hyland; D Mariotti; W Dubitzky; JAD McLaughlin; PD Maguire

Gas recognition using a neural network approach to plasma optical emission spectroscopy

M Hyland, D Mariotti, W Dubitzky, JAD McLaughlin, PD Maguire

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A system has been developed which enables the detection and recognition of various gases. Plasma emission spectroscopy has been used to record spectra from volatile species of acetone, vinegar, and coffee beans, along with air and nitrogen spectra. The spectra have been uniquely processed and fed into an artificial neural network program for training and recognition of unknown gases. The system as a whole can be grouped into the emerging and diverse area of artificial nose technology. The system has shown to provide a solution to the recognition of simple gases and odours (ait, nitrogen, acetone) and could also satisfactorily recognise more complex samples (vinegar and coffee beans). Recognition is performed in seconds; this being a positive aspect for many artificial nose applications.

Original language	English
Title of host publication	Unknown Host Publication
Editors	B Bosacchi, DB Fogel, JC Bezdek
Place of Publication	1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98227-0010 USA
Publisher	SPIE
Pages	246-252
Number of pages	5
Volume	4120
Publication status	Published - 2000
Event	APPLICATIONS AND SCIENCE OF NEURAL NETWORKS, FUZZY SYSTEMS, AND EVOLUTIONARY COMPUTATION III - SAN DIEGO Duration: 1 Jan 2000 → …

Publication series

Name	PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE)
Publisher	SPIE-INT SOC OPTICAL ENGINEERING

Conference

Conference	APPLICATIONS AND SCIENCE OF NEURAL NETWORKS, FUZZY SYSTEMS, AND EVOLUTIONARY COMPUTATION III
Period	1/01/00 → …

Fingerprint

Keywords

artificial nose
gas sensing
plasma spectroscopy
artificial neural network

Cite this

Hyland, M., Mariotti, D., Dubitzky, W., McLaughlin, JAD., & Maguire, PD. (2000). Gas recognition using a neural network approach to plasma optical emission spectroscopy. In B. Bosacchi, DB. Fogel, & JC. Bezdek (Eds.), Unknown Host Publication (Vol. 4120, pp. 246-252). (PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE)). 1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98227-0010 USA: SPIE.

Hyland, M ; Mariotti, D ; Dubitzky, W ; McLaughlin, JAD ; Maguire, PD. / Gas recognition using a neural network approach to plasma optical emission spectroscopy. Unknown Host Publication. editor / B Bosacchi ; DB Fogel ; JC Bezdek. Vol. 4120 1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98227-0010 USA : SPIE, 2000. pp. 246-252 (PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE)).

@inproceedings{b13b625eb8544cb1afcd5ed3be8b169f,

title = "Gas recognition using a neural network approach to plasma optical emission spectroscopy",

abstract = "A system has been developed which enables the detection and recognition of various gases. Plasma emission spectroscopy has been used to record spectra from volatile species of acetone, vinegar, and coffee beans, along with air and nitrogen spectra. The spectra have been uniquely processed and fed into an artificial neural network program for training and recognition of unknown gases. The system as a whole can be grouped into the emerging and diverse area of artificial nose technology. The system has shown to provide a solution to the recognition of simple gases and odours (ait, nitrogen, acetone) and could also satisfactorily recognise more complex samples (vinegar and coffee beans). Recognition is performed in seconds; this being a positive aspect for many artificial nose applications.",

keywords = "artificial nose, gas sensing, plasma spectroscopy, artificial neural network",

author = "M Hyland and D Mariotti and W Dubitzky and JAD McLaughlin and PD Maguire",

note = "Conference on Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation III, SAN DIEGO, CA, JUL 31-AUG 01, 2000",

year = "2000",

language = "English",

volume = "4120",

series = "PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE)",

publisher = "SPIE",

pages = "246--252",

editor = "B Bosacchi and DB Fogel and JC Bezdek",

booktitle = "Unknown Host Publication",

address = "United States",

}

Hyland, M, Mariotti, D, Dubitzky, W, McLaughlin, JAD & Maguire, PD 2000, Gas recognition using a neural network approach to plasma optical emission spectroscopy. in B Bosacchi, DB Fogel & JC Bezdek (eds), Unknown Host Publication. vol. 4120, PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE), SPIE, 1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98227-0010 USA, pp. 246-252, APPLICATIONS AND SCIENCE OF NEURAL NETWORKS, FUZZY SYSTEMS, AND EVOLUTIONARY COMPUTATION III, 1/01/00.

Gas recognition using a neural network approach to plasma optical emission spectroscopy. / Hyland, M; Mariotti, D; Dubitzky, W; McLaughlin, JAD ; Maguire, PD.

Unknown Host Publication. ed. / B Bosacchi; DB Fogel; JC Bezdek. Vol. 4120 1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98227-0010 USA : SPIE, 2000. p. 246-252 (PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Gas recognition using a neural network approach to plasma optical emission spectroscopy

AU - Hyland, M

AU - Mariotti, D

AU - Dubitzky, W

AU - McLaughlin, JAD

AU - Maguire, PD

N1 - Conference on Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation III, SAN DIEGO, CA, JUL 31-AUG 01, 2000

PY - 2000

Y1 - 2000

N2 - A system has been developed which enables the detection and recognition of various gases. Plasma emission spectroscopy has been used to record spectra from volatile species of acetone, vinegar, and coffee beans, along with air and nitrogen spectra. The spectra have been uniquely processed and fed into an artificial neural network program for training and recognition of unknown gases. The system as a whole can be grouped into the emerging and diverse area of artificial nose technology. The system has shown to provide a solution to the recognition of simple gases and odours (ait, nitrogen, acetone) and could also satisfactorily recognise more complex samples (vinegar and coffee beans). Recognition is performed in seconds; this being a positive aspect for many artificial nose applications.

AB - A system has been developed which enables the detection and recognition of various gases. Plasma emission spectroscopy has been used to record spectra from volatile species of acetone, vinegar, and coffee beans, along with air and nitrogen spectra. The spectra have been uniquely processed and fed into an artificial neural network program for training and recognition of unknown gases. The system as a whole can be grouped into the emerging and diverse area of artificial nose technology. The system has shown to provide a solution to the recognition of simple gases and odours (ait, nitrogen, acetone) and could also satisfactorily recognise more complex samples (vinegar and coffee beans). Recognition is performed in seconds; this being a positive aspect for many artificial nose applications.

KW - artificial nose

KW - gas sensing

KW - plasma spectroscopy

KW - artificial neural network

M3 - Conference contribution

VL - 4120

T3 - PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE)

SP - 246

EP - 252

BT - Unknown Host Publication

A2 - Bosacchi, B

A2 - Fogel, DB

A2 - Bezdek, JC

PB - SPIE

CY - 1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98227-0010 USA

ER -

Hyland M, Mariotti D, Dubitzky W, McLaughlin JAD , Maguire PD. Gas recognition using a neural network approach to plasma optical emission spectroscopy. In Bosacchi B, Fogel DB, Bezdek JC, editors, Unknown Host Publication. Vol. 4120. 1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98227-0010 USA: SPIE. 2000. p. 246-252. (PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE)).